High-speed signal-processing applications can use nonlinear filter processors to linearize analog-to-digital converters, RF (radio frequency) amplifiers, IF (intermediate frequency) amplifiers, mixers, transmit amplifiers, and entire receivers. Examples of signal-processing applications include, but are not limited to, communications, video, radar, electronic warfare, and signal intelligence. High linearity is critical to many such receiver and sensor applications, particularly for receiver systems that frequency-channelize an input signal into multiple sub-bands. The frequency-channelization process can enhance the in-band signal-to-noise ratio (SNR) by removing out-of-band noise. The higher SNR, though, then requires spurs and intermods of the sensor to be even lower in order to prevent interfering with signal detection.
Linearity is also important for receiver systems that combine signals from multiple antennas. The beam-forming process with multiple antennas can enhance SNR because the signals add coherently and noises add incoherently. Therefore, high linearity is often desirable for multiple antenna receiver systems.
The use of polynomial nonlinear filters can enhance linearity by mathematically subtracting out nonlinearities generated by the sensors. For high data rate applications, application-specific processors are often used to implement nonlinear filters because of the high computational throughput requirement. Application-specific processors are able to provide higher computational throughput and greater power efficiency than programmable processors.
Technology for implementing application-specific processors includes FPGA (Field Programmable Gate Array), standard cell, and full custom integrated circuits (ICs). In the design of such chips, important criteria include minimizing die area, maximizing clock speed, maximizing computational throughput, and minimizing power consumption. Therefore, there is a need for a nonlinear equalization processor architecture well suited for highly optimized IC level implementations that satisfy these design criteria.